The present disclosure relates generally to systems and methods for cardiac electrophysiology imaging and measurements. More particularly, the disclosure relates to systems and methods for noninvasive imaging of cardiac electrical activity, including atrial electrical activity.
Atrial arrhythmias, especially atrial fibrillation (AF), are gaining growing clinical concerns due to the prevalence within the population and the fact that they put the patient at risk of heart failure and stroke, and increase the rate of mortality. As the most common super-ventricular arrhythmia, the mechanisms of AF have long been controversial and debatable. Previous research gave rise to the hypothesis that localized sites in the atria with high-frequency activities are closely linked to sources maintaining AF, in both animal experiments and human studies. A number of studies also characterized the spatial-temporal organization of paroxysmal AF as spectrally hierarchical, featured by a left-to-right frequency gradient. Current endocardial mapping techniques are able to determine the electrograms, activation patterns, and above-mentioned frequency distribution during AF, using either non-contact mapping or sequential electroanatomical mapping methods. Although widely used clinically, this technique is invasive, requires sedation, and is limited in simultaneous and continuous bi-atrial mapping. The invasive nature substantially conflicts with the clinically-desired diagnostic information about the AF mechanism in intact human heart with continuous recording.
To address the above-mentioned issues, research interests have been focused on noninvasive analysis of surface electrocardiography (ECG). The body surface potential mapping technique is able to illustrate atrial electrical activities on the torso surface by using high-density surface electrodes. It has been used to depict surface activation wave fronts and evaluate spatial complexity and spectral variability during AF. Unfortunately, body surface potential mapping only provides information about the actual atrial electrical activities in an indirect manner, in a sense that it is over the surface of the torso instead of over the heart.
Another area of intense research interest is to combine the surface recordings and subject-specific heart-torso model to reconstruct the cardiac electrical activities by solving the inverse problem. A typical example of applications in atria is to image epicardial and endocardial activation isochrones during paced rhythm data and atrial flutter. Another study reconstructed epicardial activation maps of atrial flutter and AF by estimating epicardial potential. However, these methods do not depict the electrophysiological properties of AF from a spectral perspective and thus not able to identify the critical high-frequency sites from body surface potential mapping (BSPM).
Accordingly, there is a continuing need for systems and methods to provide accurate, insightful, and clinically-useful information related to atrial arrhythmias, especially AF.